Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A method for processing wireless body area network data, applied to a processing device for wireless body area network data, comprising: receiving or generating sampled value reference ranges; receiving sampled data from an acquisition device of wireless body area network data, and judging a sampled value reference range to which the sampled data belong according to a sampled value of the sampled data; and processing the sampled data according to the sampled value reference range to which the sampled data belong; wherein there are a plurality of the sampled value reference ranges, and different sampled value reference ranges correspond to different coding accuracies; and said processing the sampled data according to the sampled value reference range to which the sampled data belong comprises: encoding the sampled data according to a coding accuracy corresponding to the sampled value reference range to which the sampled data belong; wherein, after said encoding the sampled data according to a coding accuracy corresponding to the sampled value reference range to which the sampled data belong, the method further comprises: recording a sampled coding value and sampling time of each sampled data, and generating a sampling log; and determining a priority of the sampling log according to coding accuracy information of a sampled data coding value and sampling time information in the sampling log; wherein said determining a priority P of the sampling log is implemented through the following way: p = { 0 , A sampling log only contains a coding value with a lowest coding accuracy , ∑ j = 0 N - 1 T j T lo g , Others 1 , A sampling log contains a coding value with a highest coding accuracy , wherein T j = { 0 A coding value at time tj is a coding value with a lowest coding accuracy , t j + 1 - t j j ≠ N t cur - t j j = N T log =t cur −t first , T log is a duration of the sampling log, t cur is a current time and t first is a first sampling time of the sampling log; T j is a duration of a (j+1) th coding value in the sampling log, wherein t j is a sampling time of a (j+1) th coding value in the sampling log, j+1 denotes an item number in the sampling log and N denotes a total number of items contained in the sampling log.
A system for processing data from wearable sensors (body area network) analyzes sensor readings to intelligently manage data processing. It first defines ranges for sensor values, associating each range with a different coding accuracy level. Upon receiving sensor data, the system determines which defined range the data falls into and encodes the data using the accuracy level assigned to that range. It then creates a log of each data point, storing the encoded value and timestamp. The system prioritizes these logs: logs with only the lowest accuracy values get priority 0; logs with the highest accuracy values get priority 1; other logs get a priority calculated based on how long the values in log are not the lowest accuracy. This priority score dynamically optimizes resource usage.
2. The method according to claim 1 , wherein said processing the sampled data according to the sampled value reference range to which the sampled data belong comprises: if the sampled value reference range to which the sampled data belong is a designated normal sampled value range and satisfies a designated condition, deleting the sampled data.
The data processing system for wearable sensor data, as described previously, also includes a feature to improve efficiency by filtering out normal, expected sensor readings. If the incoming sensor data falls within a pre-defined "normal" range and meets certain other pre-defined conditions, the system simply discards that data point. This prevents unnecessary processing and storage of redundant information when the sensor is reporting values within an acceptable baseline. This filtering capability ensures the system focuses on potentially important or unusual sensor readings.
3. The method according to claim 1 , wherein, the method further comprises: if the priority is greater than a first priority threshold, notifying the acquisition device to shorten a data sampling period; and if the priority is smaller than or equal to the first priority threshold, notifying the acquisition device to prolong the sampling period or maintain the sampling period unchanged.
In the wearable sensor data processing system, the calculated priority of the data logs is used to dynamically adjust the sensor's data sampling rate. If the log priority exceeds a defined high-priority threshold, the system instructs the sensor to sample data more frequently, increasing the resolution of the data stream. Conversely, if the log priority is below this threshold, the system tells the sensor to reduce the sampling rate, conserving power and bandwidth. This real-time adjustment to sampling rate allows the system to focus resources on periods of high activity or anomalous readings.
4. The method according to claim 3 , wherein, after said determining a priority of the sampling log according to coding accuracy information of a sampled data coding value and the sampling time information in the sampling log, the method further comprises: if the priority is greater than a second priority threshold, shortening a data transmission period; and if the priority is smaller than or equal to the second priority threshold, prolonging the transmission period or maintaining the transmission period unchanged.
The wearable sensor data processing system, already capable of adjusting the sensor's sampling rate based on data log priority, further uses this priority to control the rate at which data is transmitted from the sensor. If the log priority exceeds a specified threshold, the system increases the data transmission frequency, allowing for near-real-time analysis of critical events. Conversely, if the priority falls below the threshold, the transmission rate is reduced, minimizing power consumption and network congestion. This dual-level control (sampling and transmission) provides granular control over the data flow.
5. A processing device for wireless body area network data, comprising hardware performing instructions stored in a non-transitory computer readable medium which executes steps in the following modules: a first module configured to receive or generate sampled value reference ranges; a second module configured to receive sampled data from an acquisition device of wireless body area network data, and judge a sampled value reference range to which the sampled data belong according to a sampled value of the sampled data; and a third module configured to process the sampled data according to the sampled value reference range to which the sampled data belong; the first module being configured such that there are a plurality of sampled value reference ranges received or generated, different sampled value reference ranges correspond to different coding accuracies; and the third module being configured such that processing the sampled data according to the sampled value reference range to which the sampled data belong comprises: encoding the sampled data according to a coding accuracy corresponding to the sampled value reference range to which the sampled data belong; wherein the third module is configured to, after encoding the sampled data according to a coding accuracy corresponding to the sampled value reference range to which the sampled data belong, further record a sampled coding value and sampling time of each sampled data, and generate a sampling log; determine a priority of the sampling log according to coding accuracy information of a sampled data coding value and sampling time information in the sampling log; the third module is configured to determine a priority P of the sampling log through the following way: p = { 0 , A sampling log only contains a coding value with a lowest coding accuracy , ∑ j = 0 N - 1 T j T lo g , Others 1 , A sampling log contains a coding value with a highest coding accuracy , wherein, T j = { 0 A coding value at time tj is a coding value with a lowest coding accuracy , t j + 1 - t j j ≠ N t cur - t j j = N T log =t cur −t first , T log is a duration of the sampling log, t cur is a current time and t first is a first sampling time of the sampling log; T j is a duration of a (j+1) th coding value in the sampling log, wherein t j is a sampling time of a (j+1) th coding value in the sampling log, j+1 denotes an item number in the sampling log and N denotes a total number of items contained in the sampling log.
A device processes wireless body area network data by using software modules. The first module receives or generates value ranges for sampled sensor data. Each range is associated with a specific coding accuracy. The second module receives sensor data and determines the corresponding range based on the sampled value. The third module processes the sensor data based on its range. This processing involves encoding the data according to the range's coding accuracy. It then records the encoded data and timestamp in a log. This log's priority is determined based on the coding accuracy and time information: priority is 0 if log only has the lowest accuracy; 1 if it contains the highest accuracy. Otherwise, priority is calculated based on how long the values in log are not the lowest accuracy.
6. The device according to claim 5 , wherein, the third module is configured such that processing the sampled data according to the sampled value reference range to which the sampled data belong comprises: if the sampled value reference range to which the sampled data belong is a designated normal sampled value range and satisfies a designated condition, deleting the sampled data.
The wearable sensor data processing device, as previously described, has its third module configured to perform data filtering. Specifically, if the received data falls within a pre-defined "normal" range and satisfies predetermined conditions, the third module is programmed to delete this data. This prevents the accumulation of redundant information and optimizes the system's processing capabilities by focusing on potentially significant or abnormal readings. This behavior is controlled by code instructions within the third module.
7. The device according to claim 5 , wherein, the third module is configured to, if the priority is greater than a first priority threshold, notify the acquisition device to shorten a data sampling period, and if the priority is smaller than or equal to the first priority threshold, notify the acquisition device to prolong the sampling period or maintain the sampling period unchanged.
The wearable sensor data processing device's third module is programmed to dynamically adjust the sensor's sampling period. If the calculated data log priority exceeds a first defined threshold, the device instructs the sensor to shorten the sampling period, increasing data resolution. Conversely, if the priority is lower than or equal to this threshold, the device tells the sensor to either prolong the sampling period (reducing data frequency) or maintain the current sampling period, conserving power and bandwidth when high-resolution data isn't required.
8. The device according to claim 7 , wherein, the third module is configured to, after determining a priority of the sampling log according to coding accuracy information of a sampled data coding value and the sampling time information in the sampling log, further, if the priority is greater than a second priority threshold, shorten a data transmission period; and if the priority is smaller than or equal to the second priority threshold, prolong the transmission period or maintain the transmission period unchanged.
In the wearable sensor data processing device, the third module not only controls the sampling rate but also manages the data transmission period. Following the calculation of the data log priority, if the priority exceeds a second threshold, the third module shortens the data transmission period, facilitating faster analysis. Conversely, if the priority is below or equal to the threshold, the module either extends the transmission period or maintains the existing period, reducing power consumption and optimizing network usage under normal conditions.
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September 19, 2017
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